Field
Embodiments described herein generally relate to data analysis systems, and more particularly, to generating symbols based on input data to be used in a neuro-linguistic behavioral recognition system.
Description of the Related Art
Many currently available surveillance and monitoring systems (e.g., video surveillance systems, SCADA monitoring systems, and the like) are trained to observe specific activities or patterns and alert an administrator when an occurrence of a predefined activity or pattern is detected. However, such systems require advance knowledge of what actions and/or objects to observe. The activities may be hard-coded into underlying applications or the system may train itself based on provided definitions. In other words, unless the underlying code includes descriptions of certain behaviors, the system is incapable of recognizing such behaviors.
In addition, many monitoring systems, e.g., video surveillance systems, require a significant amount of computing resources, including processor power, storage, and bandwidth. For example, typical video surveillance systems require a large amount of computing resources per camera feed because of the typical size of video data. Given the cost of the resources, such systems are difficult to scale.